Data is so important that it has become the new currency. From data analytics to data engineering, everything is dependent on data. The data is turned into information that further provides insight and helps in making business more successful.
Data allows the owners to make more informed decisions that will benefit their business in many ways, like improved customer experience and achievement of various organizational objectives. Data engineers are often confused with data scientists and data analysts but let’s look at its proper definition.
The key term in data engineering is engineering. Just like engineers design and build things, the job of data engineers is to design and build a pipeline that ensures that by the time the data reaches the end users, it is in a proper format and can be used easily.
These pipelines take data from different sources and collect and store them in a single warehouse that represents data as the single source of truth.
All this may sound simple, but the job requires good data literacy skills, and this is the reason for the shortage of data engineers.
Job Description Of Data Engineers
The companies expect the data engineers to perform the following roles and responsibilities:
- Working on Data Architecture
The data engineers have to use a systematic approach to plan, create and maintain data architectures while keeping the data relevant to business requirements and goals.
- Collection of Data
Before they can do any work, the data engineers need to collect relevant data from reliable and right sources.
- Conducting Researches
Data engineers also conduct research in the industry to help solve any issue that may arise while tackling a business problem.
- Improving Skills
Data engineers do not rely on theoretical concepts only. They must have advanced and up-to-date knowledge to work in any environment, irrespective of the coding language they use. Similarly, they must be equipped with the latest machine learning and its algorithms like the random forest, decision tree, k-means, etc
They must be proficient in the use of tools like Tableau, Knime, Apache Spark, etc., as they use these tools to generate valuable business insights for all types of industries.
For example, in the medical industry, data engineers can bring a big change by identifying different patterns in patient behavior to perform a diagnosis of a certain problem. Similarly, law enforcement engineers can affect crime rates at a huge level.
- Creating models and identifying different problems
Data engineers require a data model for data aggregation to extract useful information gathered in the past. They make predictive tools in which they apply forecasting techniques to get a peep into the future and make correct decisions and actions.
Similar to this, they use a prescriptive model that allows users to benefit from recommendations for different outcomes. A huge amount of time for data engineers goes into identifying the hidden patterns in stored data.
- Automation of tasks
Data engineers search the data and pinpoint those tasks where manual involvement can be eliminated, and the task can be done using automation.
Why Are Data Engineers Important to an Organization?
Data engineers take data from different sources. These sources also include databases, which can be SQL servers, Oracle DB, MySQL, Excel, or any other storing and processing software. After collection, they have to apply various algorithms to this data to make it useful so that the data can assist different departments, like marketing, sales, finance, etc., to improve the productivity of their work.
Data engineers are given the supreme job of data and are trusted with the analytics of the organization. Businesses find it hard to make real-time decisions and accurately estimate things like fraud, customer retention, etc. this is where data engineers come into work. For example, a data engineer can tell an e-commerce website which of their products will be in demand in the future. It will also help them in targeting their target audience and deliver more personalized experiences to them.
Now the world is running with the help of data, so it is only right that a professional gets a certificate data engineering. A certificate data engineering will help in making better and more accurate predictions.
There are many courses available both online and offline if you want to gain these skills. Some best data engineering courses are:
- Data Engineer Nanodegree Program (Udacity)
- Data Engineering (IBM)
- Data Engineer with Python (DataCamp)
- Data Engineering Career Path (Dataquest)
- Postgres For Data Engineers (Dataquest)
The Skills required to become a data engineer are:
SQL is the basic requirement if you want to become a data engineer. You will not be able to manage a relational database management system if you don’t know anything about SQL. To learn SQL, you will be needed to go through an extensive list of queries. Learning SQL does not only include memorizing a query but also learning about how to issue optimized queries.
- Data Warehousing
Learning to build and work with data warehouses is an essential skill for data engineers. Data warehousing assists data engineers in aggregating unstructured data, which is collected from multiple sources. This data is then compared and assessed, which will ultimately be used to improve the efficiency of business operations.
- Data Architecture
Data engineers must know how to build complex database systems for businesses. Data engineers deal with those operations that are used to tackle data that is in motion, at rest and datasets.
To work with all types of applications that are web, mobile, desktop, etc., the data engineer must have strong coding and programming skills. For this, learning languages like Java or C# is perfect. However, Python is the undefeatable champion, and its advanced level can benefit in a variety of data-related operations.
This field is highly understaffed and has a lot of scope for professionals. Doing courses and becoming prominent in this field will benefit a professional to a great extent.
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